Aberration engine

ABSTRACT

An aberration engine that collects data sensed by a monitoring system that monitors a property of a user and aggregates the collected data over a period of a time. The aberration engine detects, within the aggregated data, patterns of recurring events and, based on detecting the patterns of recurring events within the aggregated data, takes action related to the monitoring system based on the detected patterns of recurring events within the aggregated data.

CROSS REFERENCE TO RELATED APPLICATIONS

The present application claims the benefit of U.S. ProvisionalApplication No. 61/532,603, filed Sep. 9, 2011, which is incorporatedherein by reference in its entirety for all purposes.

TECHNICAL FIELD

This disclosure relates to monitoring technology and, for example,detecting events based on a pattern of past monitoring activity.

BACKGROUND

Many people equip homes and businesses with alarm systems to provideincreased security for their homes and businesses. Alarm systems mayinclude control panels that a person may use to control operation of thealarm system and sensors that monitor for security breaches. In responseto an alarm system detecting a security breach, the alarm system maygenerate an audible alert and, if the alarm system is monitored by amonitoring service, the alarm system may send electronic data to themonitoring service to alert the monitoring service of the securitybreach.

SUMMARY

Techniques are described for monitoring technology. For example,techniques are described for detecting events based on a pattern of pastmonitoring activity.

Implementations of the described techniques may include hardware, amethod or process implemented at least partially in hardware, or acomputer-readable storage medium encoded with executable instructionsthat, when executed by a processor, perform operations.

The details of one or more implementations are set forth in theaccompanying drawings and the description below. Other features will beapparent from the description and drawings, and from the claims.

DESCRIPTION OF DRAWINGS

FIGS. 1A-1C illustrate examples of using patterns of recurring events tocontrol monitoring system operations.

FIG. 2 illustrates an example system.

FIGS. 3, 8, 10, and 12 are flow charts of example processes.

FIGS. 4 and 9 illustrate example data records.

FIGS. 5-7, 11, 13, and 14 illustrate example interfaces.

DETAILED DESCRIPTION

Techniques are described for detecting abnormal activity in a propertymonitored by a monitoring (e.g., security) system even when themonitoring (e.g., security) system has not been armed by a user. Forinstance, an aberration engine monitors events detected by a securitysystem and attempts to detect abnormal activity even when the securitysystem is unarmed. Each event will get an “abnormality score” (more thanjust true/false), and a bunch of slightly suspicious events in a shortperiod of time will aggregate to cause the engine to alert the user. Inthis regard, the security system may be helpful in monitoring theproperty even when the user forgets to arm the security system and thesecurity system otherwise would not detect an alarm event.

FIGS. 1A-1C illustrate examples of using patterns of recurring events tocontrol monitoring system operations. As shown in FIG. 1A, a property 10(e.g., a home) of a user 50 is monitored by an in-home monitoring system(e.g., in-home security system) that includes components that are fixedwithin the property 10. The in-home monitoring system includes a controlpanel 20, a front door sensor 22, a motion sensor 24, and a back doorsensor 26. The front door sensor 22 is a contact sensor positioned at afront door of the property 10 and configured to sense whether the frontdoor is in an open position or a closed position. The motion sensor 24is configured to sense a moving object within the property 10. The backdoor sensor 26 is a contact sensor positioned at a back door of theproperty 10 and configured to sense whether the back door is in an openposition or a closed position.

The control panel 20 communicates over a short-range wired or wirelessconnection with each of the front door sensor 22, the motion sensor 24,and the back door sensor 26 to receive sensor data descriptive of eventsdetected by the front door sensor 22, the motion sensor 24, and the backdoor sensor 26. The control panel 20 also communicates over a long-rangewired or wireless connection with a monitoring server 30. The monitoringserver 30 is located remote from the property 10 and manages the in-homemonitoring system at the property 10, as well as other (and, perhaps,many more) in-home monitoring systems located at different propertiesthat are owned by different users. The monitoring server 30 receives,from the control panel 20, sensor data descriptive of events detected bythe sensors included in the in-home monitoring system of the property10.

In the example shown in FIG. 1A, the monitoring server 30 collects andaggregates sensor data received from the control panel 20 over a periodof time. The period of time may be relatively long and may includesensor data collected over the course of several days, several weeks,several months, and even several years. And, the aggregated sensor datamay include all events sensed by the in-home monitoring system duringthe period of time, regardless of whether the in-home monitoring systemwas armed in a manner in which the in-home monitoring system detectsalarm conditions when the events occurred. The monitoring server 30analyzes the aggregated sensor data with other data available to themonitoring server 30, such as location data for the user 50, and, basedon the analysis, detects patterns of recurring events within theaggregated sensor data and the other data available to the monitoringserver 30. The recurring events may be positive events tied to activityin the property detected by the in-home monitoring system or may benegative events that reflect a lack of activity (or a lack of aparticular type of activity) in the property detected by the in-homemonitoring system.

After detecting patterns of recurring events within the aggregatedsensor data and the other data available to the monitoring server 30,the monitoring server 30 stores the detected patterns 40 in electronicstorage accessible to the monitoring server 30. As shown in the detectedpatterns 40, the monitoring server 30 has detected a pattern that, onMonday to Thursday between eight in the morning and five in theafternoon, no door activity exists and a location of the user 50 is awayfrom the property 10. The monitoring server 30 also has detected apattern that a back door open event detected by the back door sensor 26is typically (e.g., always) proceeded by an interior motion detection bythe motion sensor 24. The monitoring server 30 further has detected apattern that, on Monday to Thursday between five and six in theafternoon, the front door sensor 22 detects opening of the front doorand a location of the user 50 at the property 10.

The monitoring server 30 uses the detected patterns 40 to performoperations related to the in-home monitoring system without requiringinput from the user 50 to define rules for the detected patterns. Forexample, in the example shown in FIG. 1A, the control panel 20 detects afront door open event on a Tuesday at 11 AM based on output from thefront door sensor 22. In this example, the control panel 20 does notdetect an alarm condition based on the front door open event because thein-home monitoring system is in an unarmed state (e.g., the user 50forgot to arm the in-home monitoring system upon leaving). The controlpanel 20 sends a message to the monitoring server 30 indicatingdetection of the front door open event on Tuesday at 11 AM at a timewhen the in-home monitoring system is in an unarmed state. Themonitoring server 30 receives the message from the control panel 20 andcompares the front door open event on Tuesday at 11 AM with the detectedpatterns 40 that were automatically identified by the monitoring server30 based on past sensor and other activity collected by the monitoringserver 30. Based on the comparison, the monitoring server 30 determinesthat the front door open event on Tuesday at 11 AM conflicts with thefirst detected pattern of no door activity on Monday to Thursday betweeneight in the morning and five in the afternoon.

To confirm whether the first detected pattern is violated, themonitoring server 30 determines a location of the user 50 based on alocation of the user's mobile phone 60. The monitoring server 30 maydetermine the location of the user's mobile phone 60 based on GlobalPositioning System (GPS) data captured by the mobile phone 60 and sentto the monitoring server 30 over a long-range wireless network (e.g.,Cellular network). Based on the determined location of the user 50, themonitoring server 30 determines that the user is away from the property10 and, therefore, the first detected pattern has been violated.Accordingly, the monitoring server 30 determines that the front dooropen event on Tuesday at 11 AM detected by the control panel 20 isabnormal and sends an alert to the user 50 indicating the abnormal frontdoor opening. At this time, the monitoring server 30 withholds alertinga central monitoring station server 70 used by a central monitoringstation that handles dispatching of emergency services based on alarmconditions detected by monitoring systems. The monitoring server 30 maywithhold alerting the central monitoring station server 70 because,although the front door open event is abnormal, the front door openevent does not have a high enough degree of abnormality to warrantcontacting the central monitoring station server 70 without firstalerting the user 50.

The user 50 may view the alert on the mobile phone 60 and take actionwith respect to the abnormal front door opening. For example, the user50 may provide user input indicating that the abnormal front dooropening is an actual alarm condition or that the abnormal front dooropening is not an alarm condition and should be ignored by themonitoring system. In this example, the mobile phone 60 receives theuser input provided by the user 50 and communicates the received userinput to the monitoring server 30. The monitoring server 30 receives theuser input from the mobile phone 60 and, in this case, ignores theabnormal front door opening because the user 50 confirmed that theabnormal front door opening was not an alarm condition.

In the example shown in FIG. 1B, the control panel 20 detects a backdoor open event on a Wednesday at 2 PM based on output from the backdoor sensor 26. The control panel 20 also detects an interior motionsensor event following the back door open event based on output from themotion sensor 24. In this example, the control panel 20 does not detectan alarm condition based on the back door open event and the motionsensor event because the in-home monitoring system is in an unarmedstate (e.g., the user 50 forgot to arm the in-home monitoring systemupon leaving). The control panel 20 sends a message to the monitoringserver 30 indicating detection of the back door open event on Wednesdayat 2 PM followed by the motion sensor event at a time when the in-homemonitoring system is in an unarmed state. The monitoring server 30receives the message from the control panel 20 and compares the backdoor open event on Wednesday at 2 PM followed by the motion sensor eventwith the detected patterns 40 that were automatically identified by themonitoring server 30 based on past sensor and other activity collectedby the monitoring server 30. Based on the comparison, the monitoringserver 30 determines that the back door open event on Wednesday at 2 PMconflicts with the first detected pattern of no door activity on Mondayto Thursday between eight in the morning and five in the afternoon anddetermines that the order of the back door open event followed by themotion sensor event conflicts with the second detected pattern of a backdoor open event typically (e.g., always) proceeded by an interior motionsensor event.

The monitoring server 30 also determines that the user 50 is away fromthe property 10 and, therefore, confirms that the first detected patternand the second detected pattern have been violated. Accordingly, themonitoring server 30 determines that the back door open event onWednesday at 2 PM followed by the motion sensor event is highlyabnormal, as it conflicts with two detected patterns of activity. Basedon the determination of highly abnormal activity, the monitoring server30 sends an alert to the central monitoring station server 70 toindicate a highly abnormal back door entry that needs investigation. Inresponse to the alert, personnel at the central monitoring station takeaction to confirm whether the highly abnormal back door entry is anactual alarm condition and dispatch emergency personnel to the property10, as needed. In this regard, even though the in-home monitoring systemis in an unarmed state, the in-home monitoring system is still effectivein detecting alarm conditions because the monitoring server 30 is ableto detect highly abnormal events and take appropriate action.

In addition, the monitoring server 30 sends an alert to the user 50indicating that the central monitoring station server 70 has beenalerted to a highly abnormal back door entry. The user 50 may view thealert on the mobile phone 60 and take action with respect to the highlyabnormal back door entry. For example, the user 50 may provide userinput indicating that the highly abnormal back door entry is an actualalarm condition or that the abnormal back door opening is not an alarmcondition. In this example, the mobile phone 60 receives the user inputprovided by the user 50 and communicates the received user input to themonitoring server 30. The monitoring server 30 receives the user inputfrom the mobile phone 60 and communicates the user input to the centralmonitoring station server 70 to assist the central monitoring stationserver 70 in determining whether the highly abnormal back door entry isan actual alarm condition.

In some implementations, rather than alerting the central stationdirectly in response to the determination of highly abnormal activity,the monitoring server 30 may first control the control panel 20 to soundan alarm at the property 10 (e.g., activate a siren) and provide theuser 50 (or another person located at the property 10) a chance todisarm the alarm before notifying the central station. In theseimplementations, the monitoring server 30 waits a predetermined periodof time (e.g., one minute), monitors for input disarming the alarm, andalerts the central monitoring station server 70 in response to adetermination that the predetermined period of time has passed withoutreceipt of input disarming the alarm.

In the example shown in FIG. 1C, the control panel 20 detects a frontdoor open event on a Thursday at 5:30 PM based on output from the frontdoor sensor 22. In this example, the control panel 20 detects an alarmcondition based on the front door open event because the in-homemonitoring system is in an armed state. The control panel 20 sends amessage to the monitoring server 30 indicating an alarm condition due todetection of the front door open event on Thursday at 5:30 PM at a timewhen the in-home monitoring system is in an armed state. The monitoringserver 30 receives the message from the control panel 20 and comparesthe front door open event on Thursday at 5:30 PM with the detectedpatterns 40 that were automatically identified by the monitoring server30 based on past sensor and other activity collected by the monitoringserver 30. Based on the comparison, the monitoring server 30 determinesthat the front door open event on Thursday at 5:30 PM is consistent withthe third detected pattern that, on Monday to Thursday between five andsix in the afternoon, the front door sensor 22 detects opening of thefront door.

To confirm whether the front door open event on Thursday at 5:30 PM isconsistent with the third detected pattern, the monitoring server 30determines a location of the user 50 based on a location of the user'smobile phone 60. Based on the determined location of the user 50, themonitoring server 30 determines that the user is at the property 10 and,therefore, the front door open event on Thursday at 5:30 PM isconsistent with the third detected pattern. Accordingly, the monitoringserver 30 determines that the front door open event on Thursday at 5:30PM is consistent with the third detected pattern detected by the controlpanel 20 is normal and determines to delay reporting of the alarmcondition to the central monitoring station server 70, thereby enablingthe user 50 more time to disable the alarm condition and, potentially,reducing the chance of reporting a false alarm. In this regard, themonitoring server 30 sends a message to the control panel 20 indicatingthat the control panel should extend the dialer delay to provide theuser 50 more time to enter a passcode needed to disarm the in-homemonitoring system and also prompt the user 50 to provide input to disarmthe in-home monitoring system. If the control panel 20 does not receiveinput to disarm the in-home monitoring system prior to expiration of theextended dialer delay period, the control panel 20 alerts the centralmonitoring station server 70 to the detected alarm condition.

FIG. 2 illustrates an example of an electronic system 200 configured toprovide surveillance and reporting. The electronic system 200 includes anetwork 105, a monitoring system control unit 110, one or more userdevices 140, 150, a monitoring application server 160, and a centralalarm station server 170. In some examples, the network 105 facilitatescommunications between the monitoring system control unit 110, the oneor more user devices 140, 150, the monitoring application server 160,and the central alarm station server 170.

The network 105 is configured to enable exchange of electroniccommunications between devices connected to the network 105. Forexample, the network 105 may be configured to enable exchange ofelectronic communications between the monitoring system control unit110, the one or more user devices 140, 150, the monitoring applicationserver 160, and the central alarm station server 170. The network 105may include, for example, one or more of the Internet, Wide AreaNetworks (WANs), Local Area Networks (LANs), analog or digital wired andwireless telephone networks (e.g., a public switched telephone network(PSTN), Integrated Services Digital Network (ISDN), a cellular network,and Digital Subscriber Line (DSL)), radio, television, cable, satellite,or any other delivery or tunneling mechanism for carrying data. Network105 may include multiple networks or subnetworks, each of which mayinclude, for example, a wired or wireless data pathway. The network 105may include a circuit-switched network, a packet-switched data network,or any other network able to carry electronic communications (e.g., dataor voice communications). For example, the network 105 may includenetworks based on the Internet protocol (IP), asynchronous transfer mode(ATM), the PSTN, packet-switched networks based on IP, X.25, or FrameRelay, or other comparable technologies and may support voice using, forexample, VoIP, or other comparable protocols used for voicecommunications. The network 105 may include one or more networks thatinclude wireless data channels and wireless voice channels. The network105 may be a wireless network, a broadband network, or a combination ofnetworks including a wireless network and a broadband network.

The monitoring system control unit 110 includes a controller 112 and anetwork module 114. The controller 112 is configured to control amonitoring system (e.g., a home alarm or security system) that includesthe monitoring system control unit 110. In some examples, the controller112 may include a processor or other control circuitry configured toexecute instructions of a program that controls operation of an alarmsystem. In these examples, the controller 112 may be configured toreceive input from sensors, detectors, or other devices included in thealarm system and control operations of devices included in the alarmsystem or other household devices (e.g., a thermostat, an appliance,lights, etc.). For example, the controller 112 may be configured tocontrol operation of the network module 114 included in the monitoringsystem control unit 110.

The network module 114 is a communication device configured to exchangecommunications over the network 105. The network module 114 may be awireless communication module configured to exchange wirelesscommunications over the network 105. For example, the network module 114may be a wireless communication device configured to exchangecommunications over a wireless data channel and a wireless voicechannel. In this example, the network module 114 may transmit alarm dataover a wireless data channel and establish a two-way voice communicationsession over a wireless voice channel. The wireless communication devicemay include one or more of a GSM module, a radio modem, cellulartransmission module, or any type of module configured to exchangecommunications in one of the following formats: GSM or GPRS, CDMA, EDGEor EGPRS, EV-DO or EVDO, UMTS, or IP.

The network module 114 also may be a wired communication moduleconfigured to exchange communications over the network 105 using a wiredconnection. For instance, the network module 114 may be a modem, anetwork interface card, or another type of network interface device. Thenetwork module 114 may be an Ethernet network card configured to enablethe monitoring system control unit 110 to communicate over a local areanetwork and/or the Internet. The network module 114 also may be avoiceband modem configured to enable the alarm panel to communicate overthe telephone lines of Plain Old Telephone Systems (POTS).

The monitoring system that includes the monitoring system control unit110 includes one or more sensors or detectors. For example, themonitoring system may include multiple sensors 120. The sensors 120 mayinclude a contact sensor, a motion sensor, a glass break sensor, or anyother type of sensor included in an alarm system or security system. Thesensors 120 also may include an environmental sensor, such as atemperature sensor, a water sensor, a rain sensor, a wind sensor, alight sensor, a smoke detector, a carbon monoxide detector, an airquality sensor, etc. The sensors 120 further may include a healthmonitoring sensor, such as a prescription bottle sensor that monitorstaking of prescriptions, a blood pressure sensor, a blood sugar sensor,a bed mat configured to sense presence of liquid (e.g., bodily fluids)on the bed mat, etc. In some examples, the sensors 120 may include aradio-frequency identification (RFID) sensor that identifies aparticular article that includes a pre-assigned RFID tag.

The monitoring system control unit 110 communicates with the module 122and the camera 130 to perform surveillance or monitoring. The module 122is connected to one or more lighting systems and is configured tocontrol operation of the one or more lighting systems. The module 122may control the one or more lighting systems based on commands receivedfrom the monitoring system control unit 110. For instance, the module122 may cause a lighting system to illuminate an area to provide abetter image of the area when captured by a camera 130.

The camera 130 may be a video/photographic camera or other type ofoptical sensing device configured to capture images. For instance, thecamera 130 may be configured to capture images of an area within abuilding monitored by the monitoring system control unit 110. The camera130 may be configured to capture single, static images of the area andalso video images of the area in which multiple images of the area arecaptured at a relatively high frequency (e.g., thirty images persecond). The camera 130 may be controlled based on commands receivedfrom the monitoring system control unit 110.

The camera 130 may be triggered by several different types oftechniques. For instance, a Passive Infra Red (PIR) motion sensor may bebuilt into the camera 130 and used to trigger the camera 130 to captureone or more images when motion is detected. The camera 130 also mayinclude a microwave motion sensor built into the camera and used totrigger the camera 130 to capture one or more images when motion isdetected. The camera 130 may have a “normally open” or “normally closed”digital input that can trigger capture of one or more images whenexternal sensors (e.g., the sensors 120, PIR, door/window, etc.) detectmotion or other events. In some implementations, the camera 130 receivesa command to capture an image when external devices detect motion oranother potential alarm event. The camera 130 may receive the commandfrom the controller 112 or directly from one of the sensors 120.

In some examples, the camera 130 triggers integrated or externalilluminators (e.g., Infra Red, Z-wave controlled “white” lights, lightscontrolled by the module 122, etc.) to improve image quality when thescene is dark. An integrated or separate light sensor may be used todetermine if illumination is desired and may result in increased imagequality.

The camera 130 may be programmed with any combination of time/dayschedules, system “arming state”, or other variables to determinewhether images should be captured or not when triggers occur. The camera130 may enter a low-power mode when not capturing images. In this case,the camera 130 may wake periodically to check for inbound messages fromthe controller 112. The camera 130 may be powered by internal,replaceable batteries if located remotely from the monitoring controlunit 110. The camera 130 may employ a small solar cell to recharge thebattery when light is available. Alternatively, the camera 130 may bepowered by the controller's 112 power supply if the camera 130 isco-located with the controller 112.

The sensors 120, the module 122, and the camera 130 communicate with thecontroller 112 over communication links 124, 126, and 128. Thecommunication links 124, 126, and 128 may be a wired or wireless datapathway configured to transmit signals from the sensors 120, the module122, and the camera 130 to the controller 112. The sensors 120, themodule 122, and the camera 130 may continuously transmit sensed valuesto the controller 112, periodically transmit sensed values to thecontroller 112, or transmit sensed values to the controller 112 inresponse to a change in a sensed value.

The communication link 128 over which the camera 130 and the controller112 communicate may include a local network. The camera 130 and thecontroller 112 may exchange images and commands over the local network.The local network may include 802.11 “WiFi” wireless Ethernet (e.g.,using low-power WiFi chipsets), Z-Wave, Zigbee, Bluetooth, “Homeplug” orother “Powerline” networks that operate over AC wiring, and a Category 5(CATS) or Category 6 (CAT6) wired Ethernet network.

The monitoring application server 160 is an electronic device configuredto provide monitoring services by exchanging electronic communicationswith the monitoring system control unit 110, the one or more userdevices 140, 150, and the central alarm station server 170 over thenetwork 105. For example, the monitoring application server 160 may beconfigured to monitor events (e.g., alarm events) generated by themonitoring system control unit 110. In this example, the monitoringapplication server 160 may exchange electronic communications with thenetwork module 114 included in the monitoring system control unit 110 toreceive information regarding events (e.g., alarm events) detected bythe monitoring system control unit 110. The monitoring applicationserver 160 also may receive information regarding events (e.g., alarmevents) from the one or more user devices 140, 150.

In some examples, the monitoring application server 160 may route alarmdata received from the network module 114 or the one or more userdevices 140, 150 to the central alarm station server 170. For example,the monitoring application server 160 may transmit the alarm data to thecentral alarm station server 170 over the network 105.

The monitoring application server 160 may store sensor and image datareceived from the monitoring system and perform analysis of sensor andimage data received from the monitoring system. Based on the analysis,the monitoring application server 160 may communicate with and controlaspects of the monitoring system control unit 110 or the one or moreuser devices 140, 150.

The central alarm station server 170 is an electronic device configuredto provide alarm monitoring service by exchanging communications withthe monitoring system control unit 110, the one or more mobile devices140, 150, and the monitoring application server 160 over the network105. For example, the central alarm station server 170 may be configuredto monitor alarm events generated by the monitoring system control unit110. In this example, the central alarm station server 170 may exchangecommunications with the network module 114 included in the monitoringsystem control unit 110 to receive information regarding alarm eventsdetected by the monitoring system control unit 110. The central alarmstation server 170 also may receive information regarding alarm eventsfrom the one or more mobile devices 140, 150.

The central alarm station server 170 is connected to multiple terminals172 and 174. The terminals 172 and 174 may be used by operators toprocess alarm events. For example, the central alarm station server 170may route alarm data to the terminals 172 and 174 to enable an operatorto process the alarm data. The terminals 172 and 174 may includegeneral-purpose computers (e.g., desktop personal computers,workstations, or laptop computers) that are configured to receive alarmdata from a server in the central alarm station server 170 and render adisplay of information based on the alarm data. For instance, thecontroller 112 may control the network module 114 to transmit, to thecentral alarm station server 170, alarm data indicating that a sensor120 detected a door opening when the monitoring system was armed. Thecentral alarm station server 170 may receive the alarm data and routethe alarm data to the terminal 172 for processing by an operatorassociated with the terminal 172. The terminal 172 may render a displayto the operator that includes information associated with the alarmevent (e.g., the name of the user of the alarm system, the address ofthe building the alarm system is monitoring, the type of alarm event,etc.) and the operator may handle the alarm event based on the displayedinformation.

In some implementations, the terminals 172 and 174 may be mobile devicesor devices designed for a specific function. Although FIG. 2 illustratestwo terminals for brevity, actual implementations may include more (and,perhaps, many more) terminals.

The one or more user devices 140, 150 are devices that host and displayuser interfaces. For instance, the user device 140 is a mobile devicethat hosts one or more native applications (e.g., the nativesurveillance application 142). The user device 140 may be a cellularphone or a non-cellular locally networked device with a display. Theuser device 140 may include a cell phone, a smart phone, a tablet PC, apersonal digital assistant (“PDA”), or any other portable deviceconfigured to communicate over a network and display information. Forexample, implementations may also include Blackberry-type devices (e.g.,as provided by Research in Motion), electronic organizers, iPhone-typedevices (e.g., as provided by Apple), iPod devices (e.g., as provided byApple) or other portable music players, other communication devices, andhandheld or portable electronic devices for gaming, communications,and/or data organization. The user device 140 may perform functionsunrelated to the monitoring system, such as placing personal telephonecalls, playing music, playing video, displaying pictures, browsing theInternet, maintaining an electronic calendar, etc.

The user device 140 includes a native surveillance application 142. Thenative surveillance application 142 refers to a software/firmwareprogram running on the corresponding mobile device that enables the userinterface and features described throughout. The user device 140 mayload or install the native surveillance application 142 based on datareceived over a network or data received from local media. The nativesurveillance application 142 runs on mobile devices platforms, such asiPhone, iPod touch, Blackberry, Google Android, Windows Mobile, etc. Thenative surveillance application 142 enables the user device 140 toreceive and process image and sensor data from the monitoring system.

The user device 150 may be a general-purpose computer (e.g., a desktoppersonal computer, a workstation, or a laptop computer) that isconfigured to communicate with the monitoring application server 160and/or the monitoring system control unit 110 over the network 105. Theuser device 150 may be configured to display a surveillance monitoringuser interface 152 that is generated by the user device 150 or generatedby the monitoring application server 160. For example, the user device150 may be configured to display a user interface (e.g., a web page)provided by the monitoring application server 160 that enables a user toperceive images captured by the camera 130 and/or reports related to themonitoring system. Although FIG. 2 illustrates two user devices forbrevity, actual implementations may include more (and, perhaps, manymore) or fewer user devices.

In some implementations, the one or more user devices 140, 150communicate with and receive monitoring system data from the monitoringsystem control unit 110 using the communication link 138. For instance,the one or more user devices 140, 150 may communicate with themonitoring system control unit 110 using various local wirelessprotocols such as wifi, Bluetooth, zwave, zigbee, HomePlug (ethernetover powerline), or wired protocols such as Ethernet and USB, to connectthe one or more user devices 140, 150 to local security and automationequipment. The one or more user devices 140, 150 may connect locally tothe monitoring system and its sensors and other devices. The localconnection may improve the speed of status and control communicationsbecause communicating through the network 105 with a remote server(e.g., the monitoring application server 160) may be significantlyslower.

Although the one or more user devices 140, 150 are shown ascommunicating with the monitoring system control unit 110, the one ormore user devices 140, 150 may communicate directly with the sensors andother devices controlled by the monitoring system control unit 110. Insome implementations, the one or more user devices 140, 150 replace themonitoring system control unit 110 and perform the functions of themonitoring system control unit 110 for local monitoring and longrange/offsite communication.

In other implementations, the one or more user devices 140, 150 receivemonitoring system data captured by the monitoring system control unit110 through the network 105. The one or more user devices 140, 150 mayreceive the data from the monitoring system control unit 110 through thenetwork 105 or the monitoring application server 160 may relay datareceived from the monitoring system control unit 110 to the one or moreuser devices 140, 150 through the network 105. In this regard, themonitoring application server 160 may facilitate communication betweenthe one or more user devices 140, 150 and the monitoring system.

In some implementations, the one or more user devices 140, 150 may beconfigured to switch whether the one or more user devices 140, 150communicate with the monitoring system control unit 110 directly (e.g.,through link 138) or through the monitoring application server 160(e.g., through network 105) based on a location of the one or more userdevices 140, 150. For instance, when the one or more user devices 140,150 are located close to the monitoring system control unit 110 and inrange to communicate directly with the monitoring system control unit110, the one or more user devices 140, 150 use direct communication.When the one or more user devices 140, 150 are located far from themonitoring system control unit 110 and not in range to communicatedirectly with the monitoring system control unit 110, the one or moreuser devices 140, 150 use communication through the monitoringapplication server 160.

Although the one or more user devices 140, 150 are shown as beingconnected to the network 105, in some implementations, the one or moreuser devices 140, 150 are not connected to the network 105. In theseimplementations, the one or more user devices 140, 150 communicatedirectly with one or more of the monitoring system components and nonetwork (e.g., Internet) connection or reliance on remote servers isneeded.

In some implementations, the one or more user devices 140, 150 are usedin conjunction with only local sensors and/or local devices in a house.In these implementations, the system 200 only includes the one or moreuser devices 140, 150, the sensors 120, the module 122, and the camera130. The one or more user devices 140, 150 receive data directly fromthe sensors 120, the module 122, and the camera 130 and sends datadirectly to the sensors 120, the module 122, and the camera 130. The oneor more user devices 140, 150 provide the appropriateinterfaces/processing to provide visual surveillance and reporting.

In other implementations, the system 200 further includes network 105and the sensors 120, the module 122, and the camera 130 are configuredto communicate sensor and image data to the one or more user devices140, 150 over network 105 (e.g., the Internet, cellular network, etc.).In yet another implementation, the sensors 120, the module 122, and thecamera 130 (or a component, such as a bridge/router) are intelligentenough to change the communication pathway from a direct local pathwaywhen the one or more user devices 140, 150 are in close physicalproximity to the sensors 120, the module 122, and the camera 130 to apathway over network 105 when the one or more user devices 140, 150 arefarther from the sensors 120, the module 122, and the camera 130. Insome examples, the system leverages GPS information from the one or moreuser devices 140, 150 to determine whether the one or more user devices140, 150 are close enough to the sensors 120, the module 122, and thecamera 130 to use the direct local pathway or whether the one or moreuser devices 140, 150 are far enough from the sensors 120, the module122, and the camera 130 that the pathway over network 105 is required.In other examples, the system leverages status communications (e.g.,pinging) between the one or more user devices 140, 150 and the sensors120, the module 122, and the camera 130 to determine whethercommunication using the direct local pathway is possible. Ifcommunication using the direct local pathway is possible, the one ormore user devices 140, 150 communicate with the sensors 120, the module122, and the camera 130 using the direct local pathway. If communicationusing the direct local pathway is not possible, the one or more userdevices 140, 150 communicate with the sensors 120, the module 122, andthe camera 130 using the pathway over network 105.

In some implementations, the system 200 provides end users with accessto images captured by the camera 130 to aid in decision making. Thesystem 200 may transmit the images captured by the camera 130 over awireless WAN network to the user devices 140, 150. Because transmissionover a wireless WAN network may be relatively expensive, the system 200uses several techniques to reduce costs while providing access tosignificant levels of useful visual information.

In some implementations, a state of the monitoring system and otherevents sensed by the monitoring system may be used to enable/disablevideo/image recording devices (e.g., the camera 130). In theseimplementations, the camera 130 may be set to capture images on aperiodic basis when the alarm system is armed in an “Away” state, butset not to capture images when the alarm system is armed in a “Stay”state or disarmed. In addition, the camera 130 may be triggered to begincapturing images when the alarm system detects an event, such as analarm event, a door opening event for a door that leads to an areawithin a field of view of the camera 130, or motion in the area withinthe field of view of the camera 130. In other implementations, thecamera 130 may capture images continuously, but the captured images maybe stored or transmitted over a network when needed.

In some implementations, one or more of the components of the system 200(e.g., the monitoring application server 160) may be configured tooperate as an aberration engine. The aberration engine may automaticallydetect unusual/suspicious behavior associated with a building monitoredby the system 200 and alert one or more users of the system 200 whenunusual/suspicious behavior is detected. Because many people, at times,do not arm their security systems, the aberration engine attempts todetect unusual/suspicious behavior even when the security system is notin an armed state. In this regard, the aberration engine allows asecurity system to remain useful while it is disarmed.

The aberration engine may consider any inputs and data related to thesystem 200 to detect unusual/suspicious behavior. For instance, theinputs to the aberration engine may include:

-   -   1) Historical sensor data    -   2) Current status of the security system    -   3) Other current status information        -   a. Car or smartphone locations may be considered    -   4) The customer's historical responses to aberration engine        alerts    -   5) A customer-specified level of sensitivity/risk for each        sensor, and some measure of how much false alarms bother them

The aberration engine may provide any type of output or report based ondetection of unusual/suspicious behavior. For example, the output of theaberration engine may be an alert that includes:

-   -   1) The event(s) that triggered the alert    -   2) Some measure of how unusual this behavior is based on history        of the system 200    -   3) Some actions the customer can take        -   a. Notify the Central Station        -   b. View video        -   c. Ignore it        -   d. Ignore it, and tell us not to alert about things like            this again    -   4) Activation of an alarm (e.g., siren) at a monitored property        and initiation of a dialer delay period        -   a. A user may deactivate the alarm by providing appropriate            input prior to expiration of the dialer delay period        -   b. If the dialer delay period expires prior to receipt of            input that deactivates the alarm, the central station is            notified

In operation, the aberration engine uses statistical analysis to decidewhat is “normal” and what is “abnormal.” The aberration engine may usethree main things to determine what is “normal” and what is “abnormal”:

-   -   1) Timing        -   a. If a sensor is opening at a time of day/day of week            during which it has never had any activity before, that is            abnormal.    -   2) Order of events        -   a. If there has been no activity for a long time, then the            back door opens, then the motion sensor goes off, that is            abnormal.    -   3) Other info        -   a. If the front door opens while none of the occupant's            phones/cars are near home, that is abnormal.

The aberration engine also may treat the lack of events as abnormal. Forinstance, the aberration engine may consider typical alarm system inputand typical sensed events and assess whether a lack alarm system inputor sensed events gives rise to concern. In some examples, the aberrationengine may consider the following factors:

1) If the system is typically disarmed between 3:30 and 4:30 PM, buttoday it was not, then alert.

2) If Timmy's phone typically comes from school along a certain path tohome between 3 and 4 PM and today it went somewhere else, alert.

3) If the kitchen door is normally opened shortly after the garage dooron weekday evenings, but today only the garage door was opened, alert.

The aberration engine may assign an “abnormality score” to each event(not just true/false) and determine whether unusual/suspicious behaviorhas occurred based on the abnormality scores. For example, a bunch ofslightly suspicious events (e.g., events with low to medium abnormalityscores) in a short period of time may aggregate to cause the aberrationengine to alert the user. In another example, a single event with alarge abnormality score may cause the aberration engine to alert theuser.

The aberration engine also may determine to send the alert to morepeople in a more visible way as the likelihood of a real event increasesand as the sensitivity/risk associated with the activity increases. Forexample, if the front door opens in the middle of the day on a weekday,and that happens about once per month, the aberration engine may emailthe main end user. If the back door opens in the middle of the nightwhile nobody is home and is left open for a threshold period of time,and the jewelry box is opened, the aberration engine may try to notifyall users, possibly including the central station.

The aberration engine also may be used in reverse to try to reduce thereporting of false alarms by extending the dialer delay in cases wherethe alarm goes off based on events that the aberration engine considersto be normal behavior. For example, historical data may suggest that thesystem is typically (e.g., always) disarmed between six and seven pm onweekdays. In this example, if the front door opens at six-thirty pm asis normal, but the system is not disarmed, the aberration engine wouldassess the behavior as normal and determine that the potential alarm hasa high probability of being a false alarm. Accordingly, in an effort toreduce false alarms reported to the central station, the aberrationengine would extend the dialer delay to allow more time for the user todisarm the security system.

The aberration engine may be run on the panel/firmware, on the backend,or on any other suitable component of the security system. In someexamples, functionality of the aberration engine may be distributedamong various components of the security system such that somefunctionality may be implemented by the panel/firmware and otherfunctionality may be implemented by the backend.

In some implementations, all of the processing described throughout thisdisclosure may be implemented in a monitoring system control panellocated inside the property being monitored, as opposed to sending datato an external server for processing. For example, rather than being aseparate server located in a remote location, the monitoring applicationserver 160 may be a logical component inside of the monitoring systemcontrol unit 110. In this example, the monitoring system control unit110 performs the processing of the aberration engine without having tosend sensor data to a separate server separated by a network.

In other implementations, all of the processing described throughoutthis disclosure may be performed on a remote server (e.g., monitoringapplication server 160). In these implementations, the monitoring systemcontrol panel (or sensors themselves) may send sensor data to the remoteserver over a network and the remote server may perform all of theaberration engine analysis of the sensor data. For instance, themonitoring system control unit 110 sends all captured sensor data to themonitoring application server 160 and the monitoring application server160 performs the processing of the aberration engine.

In still further implementations, the processing described throughoutthis disclosure may be mixed between a monitoring system control paneland a remote server. In these implementations, the monitoring systemcontrol panel and the remote server may share operations needed toanalyze the sensor data. For instance, the monitoring system controlpanel may perform the aberration engine analysis of the sensor datacollected relatively recently (e.g., sensor data collected within thepast three months) and the remote server may perform the aberrationengine analysis of the sensor data collected over a longer period oftime (e.g., sensor data collected over the past several years).Alternatively, the monitoring system control panel may performpre-processing of the sensor data, including collection and aggregationof the sensor data, and the remote server may perform the detailedanalysis of detecting patterns within the sensor data. In the exampleshown in FIG. 2, the processing described throughout this disclosure maybe mixed between the monitoring system control unit 110 and themonitoring application server 160.

FIGS. 3, 8, 10, and 12 illustrate example processes. The operations ofthe example processes are described generally as being performed by thesystem 200. The operations of the example processes may be performed byone of the components of the system 200 (e.g., the monitor control unit110, the monitoring application server 160, etc.) or may be performed byany combination of the components of the system 200. In someimplementations, operations of the example processes may be performed byone or more processors included in one or more electronic devices.

FIG. 3 illustrates an example process 300 for taking action related to amonitoring system based on detected patterns of recurring events withaggregated monitoring data. The system 200 collects data sensed by amonitoring system that monitors a property of a user (310). For example,the system 200 receives, over a network, data describing sensor eventsdetected by sensors fixed at the property of the user. In this example,the sensor events may be contact sensor events detected by door andwindow sensors located at doors and windows of the property, motionsensor events detected by motion sensors located at the property, andany other type of sensor events detected by other types describedthroughout this disclosure. The system 200 receives all sensor eventsdetected by the monitoring system, regardless of whether the monitoringsystem is in an armed state or an unarmed state when the sensor eventsare detected.

The system 200 aggregates the collected data over a period of a time(320). For instance, the system 200 identifies the property and/or userassociated with collected sensor events and stores sensor eventscollected over time for the identified property and/or user with anindication of the identified property and/or user. In this regard, thesystem 200 stores the collected sensor events in a manner that enablesthe system 200 to access all of the collected sensor events for theidentified property and/or user. The system 200 may aggregate thecollected sensor events over any period of time, including all sensorevents collected over years, sensor events collected over a period ofone or more months, sensor events collected over a period of one or moreweeks, or other suitable time periods that enable the system 200 todetect recurring events in the aggregated sensor data.

The system 200 detects, within the aggregated data, patterns ofrecurring events (330). For instance, the system 200 analyzes theaggregated data to detect patterns of recurring sensor events in theaggregated data. The system 200 may detect events as events sensed bysensors of the monitoring system as well as a lack of sensor eventsdetected. The system 200 may consider the timing of events, such asevents that repeat on a routine basis (e.g., events that occur at therelatively same time everyday day or events that occur at the relativelysame time on a particular day of the week). The system 200 also mayconsider orders in which events occur (e.g., a particular motion sensorevent routinely precedes a particular door open event). The order ofevents may be considered with respect to timing or irrespective oftiming.

In detecting patterns, the system 200 may consider any type ofhistorical sensor activity detected by a monitoring system located at aproperty. The system 200 also may consider other types of activity, suchas location data of one or more users of the monitoring system, datacollected by sensors of a vehicle of one or more users of the monitoringsystem, weather data accessible to the monitoring system, or any othertype of data that the system 200 is capable of collecting, aggregating,and analyzing.

To detect patterns within the aggregated data, the system 200 may useany type of data mining techniques capable of detecting patterns ofrecurring events. The system 200 may perform an automatic orsemi-automatic analysis of relatively large quantities of sensor data toextract previously unknown interesting patterns, such as identifyinggroups of sensor events using cluster analysis, identifying unusualsensor events using anomaly detection, and identifying dependenciesusing association rule mining. Based on the patterns detected, thesystem 200 may assign a confidence score for each pattern that reflectsa level of confidence that the detected pattern is actually a pattern ofrecurring events that will be observed in the future. The system 200 maydetermine the confidence score based on a percentage of time the patternhas occurred in the past, the amount of data used in detecting thepattern, and any statistical techniques that assess whether the patternis a statistically significant pattern of recurring events.

FIG. 4 illustrates an example data record 400 that stores patternsdetected within aggregated sensor data and confidence scores for each ofthe detected patterns. The data record 400 includes a first column 410for a detected pattern and a second column 420 for a confidence scoreassociated with the pattern stored in the column 410. As shown, a firstdetected pattern 430 indicates that the system 200 detected a pattern ofa lack of sensor activity on Saturdays between seven in the morning toone in the afternoon. The first detected pattern 430 has a confidencescore of sixty, which indicates that the pattern is more likely thannot, but not overly confident (e.g., no sensor activity on Saturdaysbetween seven in the morning to one in the afternoon has been detectedsixty percent of the time).

A second detected pattern 440 indicates that the system 200 detected apattern of arming the monitoring system in a “Stay” mode by eleven inthe evening when all users are detected as being at home. The seconddetected pattern 440 has a confidence score of ninety, which indicatesthat the pattern is likely (e.g., arming the monitoring system in a“Stay” mode by eleven in the evening when all users are detected asbeing at home has occurred ninety percent of the time).

A third detected pattern 450 indicates that the system 200 detected apattern of arming the monitoring system in an “Away” mode by nine in themorning when all users are detected as being away from home. The thirddetected pattern 450 has a confidence score of ninety-five, whichindicates that the pattern is likely (e.g., arming the monitoring systemin an “Away” mode by nine in the morning when all users are detected asbeing away from home has occurred ninety-five percent of the time).

A fourth detected pattern 460 indicates that the system 200 detected apattern of window opening events being preceded by interior motiondetection events. The window opening events may be for a specific windowor all windows in a monitored property. The fourth detected pattern 460has a confidence score of one hundred, which indicates that the patternis very likely (e.g., window opening events have been preceded byinterior motion detection events one hundred percent of the time).

A fifth detected pattern 470 indicates that the system 200 detected apattern of back door opening events being preceded by interior motiondetection events daily between six to seven in the morning and ten toeleven in the evening. The fifth detected pattern 470 has a confidencescore of eighty, which indicates that the pattern is likely (e.g., backdoor opening events have been preceded by interior motion detectionevents daily between six to seven in the morning and ten to eleven inthe evening eighty percent of the time).

A sixth detected pattern 480 indicates that the system 200 detected apattern of a lack of sensor activity on Sundays between eight in themorning to noon. The sixth detected pattern 480 has a confidence scoreof seventy, which indicates that the pattern is more likely than not,but not overly confident (e.g., no sensor activity on Sundays betweeneight in the morning to noon has been detected seventy percent of thetime).

In some implementations, the system 200 uses a threshold confidencescore in determining whether or not to detect and continue monitoring apattern. In these implementations, the system 200 may use a confidencescore of sixty as a threshold (e.g., patterns that occur at least sixtypercent of the time). Accordingly, patterns having a confidence scorelower than sixty are not included in the data record 400 and do notimpact the monitoring system, unless the pattern increases to warrantfurther consideration (e.g., increases to a confidence score at sixty orabove).

Referring again to FIG. 3, the system 200 takes action related to themonitoring system based on the detected patterns of recurring events(340). For instance, the system 200 may suggest rules (e.g., alerts) forthe monitoring system based on the detected patterns of recurringevents, may automatically set rules (e.g., alerts) for the monitoringsystem based on the detected patterns of recurring events, and may sendalerts to a user or a central monitoring station to indicate detectionof abnormal activity. By taking action based on the detected patterns ofrecurring events, the system 200 may enhance the ease with which a useris able to configure a monitoring system and enable a user to benefitfrom having a monitoring system, even though the user is not diligentabout arming the monitoring system and setting alerting rules for themonitoring system.

FIG. 5 illustrates an example interface 500 that makes suggestions basedon the detected patterns of recurring events. The interface 500 may bepart of a message (e.g., electronic mail message) sent to a device of auser of a monitoring system or may be displayed when the user of themonitoring system accesses a web page associated with the monitoringsystem. The system 200 may cause display of the interface 500 when newpatterns of recurring events have been detected. The system 200 maycause display of the interface 500 as part of taking action related tothe monitoring system based on the detected patterns of recurring eventsdescribed above with respect to reference numeral 340.

As shown, the interface 500 includes a list of suggested rules 510, aconfidence 520 that reflects a level of confidence of the system 200 insuggesting the rule, and a number of expected alerts 525 that reflects anumber of alerts the system 200 expects to result from the rule over agiven time period (e.g., one year). The confidence 520 and the number ofexpected alerts 525 may assist a user in determining whether or not toadopt a suggested rule. A first suggested rule is to alert the centralstation and notify the user when the system 200 detects a window openingevent without prior detection of an interior motion sensor event. Thesystem 200 suggests the first suggested rule based on the fourthdetected pattern 460 that window openings have always been preceded byinterior motion sensor events. Accordingly, the system 200 suggests thefirst suggested rule because historical sensor data confirms that it ishighly unlikely that a window opening from outside the property (e.g.,without a prior interior motion sensor event) is normal. The interface500 shows that the system 200 has a confidence level of one hundred forthe first suggested rule, which may indicate that the first suggestedrule is being suggested based on a pattern that has occurred one hundredpercent of the time. The interface 500 also shows that, based onhistorical sensor data, the system 200 expects to send zero alerts forthe first suggested rule over the course of a year.

The interface 500 includes a set control 530 that receives input to setthe first suggested rule for the monitoring system. The interface 500also includes a decline control 532 that receives input to decline thefirst suggested rule for the monitoring system. The interface 500further includes a modify control 534 that receives input to accept thefirst suggested rule for the monitoring system, but in a modifiedformat. The modify control 534 may cause display of another interfacethat enables a user to provide input to modify the first suggested ruleby adding, removing, and/or changing criteria for meeting the ruleand/or changing actions taken when the rule has been met. The system 200may consider decisions to set, decline, and modify the first suggestedrule in future suggestions made to the user.

A second suggested rule is to set an arming reminder at nine in themorning when the system 200 detects all of the users being away fromhome and detects the monitoring system being in an unarmed state. Thesystem 200 suggests the second suggested rule based on the thirddetected pattern 450 of arming the monitoring system in an “Away” modeby nine in the morning when all users are detected as being away fromhome. Accordingly, the system 200 suggests the second suggested rulebecause historical sensor data confirms that the monitoring system istypically armed by nine in the morning when all users are detected asbeing away from home. The interface 500 shows that the system 200 has aconfidence level of ninety-five for the second suggested rule, which mayindicate that the second suggested rule is being suggested based on apattern that has occurred ninety-five percent of the time. The interface500 also shows that, based on historical sensor data, the system 200expects to send two alerts for the second suggested rule over the courseof a year.

The interface 500 includes a set control 540 that receives input to setthe second suggested rule for the monitoring system. The interface 500also includes a decline control 542 that receives input to decline thesecond suggested rule for the monitoring system. The interface 500further includes a modify control 544 that receives input to accept thesecond suggested rule for the monitoring system, but in a modifiedformat. The modify control 544 may cause display of another interfacethat enables a user to provide input to modify the second suggested ruleby adding, removing, and/or changing criteria for meeting the ruleand/or changing actions taken when the rule has been met. The system 200may consider decisions to set, decline, and modify the second suggestedrule in future suggestions made to the user.

A third suggested rule is to set a notification alert when the system200 detects activity on Sunday between eight in the morning and noon.The system 200 suggests the third suggested rule based on the sixthdetected pattern 480 of a lack of sensor activity on Sundays betweeneight in the morning to noon. Accordingly, the system 200 suggests thethird suggested rule because historical sensor data confirms that themonitoring system does not typically sense activity on Sunday betweeneight in the morning and noon. The interface 500 shows that the system200 has a confidence level of seventy for the third suggested rule,which may indicate that the third suggested rule is being suggestedbased on a pattern that has occurred seventy percent of the time. Theinterface 500 also shows that, based on historical sensor data, thesystem 200 expects to send twelve alerts for the first suggested ruleover the course of a year.

The interface 500 includes a set control 550 that receives input to setthe third suggested rule for the monitoring system. The interface 500also includes a decline control 552 that receives input to decline thethird suggested rule for the monitoring system. The interface 500further includes a modify control 554 that receives input to accept thethird suggested rule for the monitoring system, but in a modifiedformat. The modify control 554 may cause display of another interfacethat enables a user to provide input to modify the third suggested ruleby adding, removing, and/or changing criteria for meeting the ruleand/or changing actions taken when the rule has been met. The system 200may consider decisions to set, decline, and modify the third suggestedrule in future suggestions made to the user.

FIG. 6 illustrates an example interface 600 that alerts a user to rulesautomatically set for a monitoring system based on the detected patternsof recurring events. The system 200 may automatically set the ruleswithout human intervention or any user input. The interface 600 may bepart of a message (e.g., electronic mail message) sent to a device of auser of a monitoring system or may be displayed when the user of themonitoring system accesses a web page associated with the monitoringsystem. The system 200 may cause display of the interface 600 when newpatterns of recurring events have been detected and new rulesautomatically set. The system 200 may cause display of the interface 600as part of taking action related to the monitoring system based on thedetected patterns of recurring events described above with respect toreference numeral 340.

As shown, the interface 600 includes a list of automatically set rules610 and a confidence 620 that reflects a level of confidence of thesystem 200 in automatically setting the rule. The confidence 620 mayassist a user in determining whether or not to confirm or remove anautomatically set rule. A first rule is to automatically arm the systemto “Stay” when all users are detected as being home and system isunarmed at 11 PM. The system 200 automatically sets the first rule basedon the second detected pattern 440 that the system 200 detected apattern of arming the monitoring system in a “Stay” mode by eleven inthe evening when all users are detected as being at home. Accordingly,the system 200 automatically set the first rule because historicalsensor data confirms that it is likely that the users of the monitoringsystem like to have the monitoring system set in the “Stay” mode byeleven in the evening when all users are detected as being at home andthe automatic arming addresses situations in which the users forget toset the monitoring system in the “Stay” mode without waking sleepingusers with an alert. The interface 600 shows that the system 200 has aconfidence level of ninety for the first rule, which may indicate thatthe first rule was automatically set based on a pattern that hasoccurred ninety percent of the time.

The interface 600 includes a confirm control 630 that receives input toconfirm that the first rule should be set for the monitoring system. Theinterface 600 also includes a remove control 632 that receives input toremove the first rule for the monitoring system. The interface 600further includes a modify control 634 that receives input to confirmthat the first rule should be set for the monitoring system, but in amodified format. The modify control 634 may cause display of anotherinterface that enables a user to provide input to modify the first ruleby adding, removing, and/or changing criteria for meeting the ruleand/or changing actions taken when the rule has been met. The system 200may consider decisions to confirm, remove, and modify the first rule infuture automatic setting of rules for the monitoring system of the user.

A second rule is to, when the system is armed “Stay,” delay activating asiren and delay alerting the central station for an alarm conditiondetected based on a back door open event when the back door open eventoccurs between 6 AM to 7 AM or 10 PM to 11 PM and is preceded by aninterior motion sensor event. The system 200 automatically sets thesecond rule based on the fifth detected pattern 470 that the system 200detected a pattern of back door opening events being preceded byinterior motion detection events daily between six to seven in themorning and ten to eleven in the evening. Accordingly, the system 200automatically set the second rule because historical sensor dataconfirms that it is likely that the user of the monitoring systemopening the back door from inside of the home between 6 AM to 7 AM or 10PM to 11 PM is normal and, therefore, the second rule gives the usermore time to disarm the monitoring system prior to taking action for analarm condition. The interface 600 shows that the system 200 has aconfidence level of eighty for the second rule, which may indicate thatthe second rule was automatically set based on a pattern that hasoccurred eighty percent of the time.

The interface 600 includes a confirm control 640 that receives input toconfirm that the second rule should be set for the monitoring system.The interface 600 also includes a remove control 642 that receives inputto remove the second rule for the monitoring system. The interface 600further includes a modify control 644 that receives input to confirmthat the second rule should be set for the monitoring system, but in amodified format. The modify control 644 may cause display of anotherinterface that enables a user to provide input to modify the second ruleby adding, removing, and/or changing criteria for meeting the ruleand/or changing actions taken when the rule has been met. The system 200may consider decisions to confirm, remove, and modify the second rule infuture automatic setting of rules for the monitoring system of the user.

FIG. 7 illustrates an example interface 700 that alerts a user toabnormal activity. The interface 700 may be part of a message (e.g.,electronic mail message) sent to a device of a user of a monitoringsystem when abnormal activity has been detected. The system 200 maycause display of the interface 700 as part of taking action related tothe monitoring system based on the detected patterns of recurring eventsdescribed above with respect to reference numeral 340.

The system 200 may detect abnormal activity based on a series of eventsthat are each slightly abnormal, but, when considered together, suggestabnormal activity. For instance, the system 200 may identify a series ofevents detected by the monitoring system and determine abnormalitymeasures based on the detected patterns of recurring events within theaggregated data. The determined abnormality measures may include anabnormality measure for each event included in the series of events. Thesystem 200 then may determine an abnormality score for the series ofevents based on the determined abnormality measures, compare theabnormality score to a threshold, and, based on the comparison,determine that the abnormality score meets the threshold (e.g., theabnormality score is greater than an abnormality threshold). Based onthe determination that the abnormality score meets the threshold, thesystem 200 may send, to the user, an alert including the interface 700,which indicates that the monitoring system has detected abnormalactivity at the property of the user.

The interface 700 includes an abnormality measure 710 that reflects alevel of abnormality represented by the series of events. Theabnormality measure 710 may be determined based on the abnormality scoreand, as shown, may be represented as a bar that reflects whether theabnormal activity is highly abnormal, moderately abnormal, or slightlyabnormal. The abnormality measure 710 provides a quick indication ofwhether the level of abnormality of the detected activity is relativelylow or relatively high and, therefore, may assist the user indetermining how closely the user reviews the alert including theinterface 700.

The interface 700 also includes a list of events 720 that resulted inthe system 200 detecting abnormal activity at the property of the user.The list of events 720 enables a user to review the sensor events thatled to the determination of abnormal activity and determine whether theevents are normal or related to an alarm condition.

The interface 700 further includes interface controls 730-760 thatenable a user to respond and handle the report of abnormal activity. Theinterface controls 730-760 include a notify central station control 730that receives user input to indicate that the user believes the abnormalactivity is an alarm condition that should be reported to the centralstation. In response to user activation of the notify central stationcontrol 730, the system 200 receives the indication that the userbelieves the abnormal activity is an alarm condition and then reportsthe alarm condition to the central station with an indication that theuser has confirmed that the activity is an alarm condition.

The interface controls 730-760 also include a view video control 740that receives user input to indicate that the user would like to viewvideo of the property to assist in determining whether the activity isnormal or an alarm condition. In response to user activation of the viewvideo control 740, the system 200 receives the indication that the userwould like to view video of the property and then sends video capturedby a camera located at the property to the user's device for viewing.After viewing the video, the user may provide additional input toindicate whether the activity is normal or an alarm condition.

The interface controls 730-760 further include an ignore control 750 andan ignore and stop alerting control 760. The ignore control 750 receivesuser input to indicate that the user would like to ignore the abnormalactivity alert, as the user believes the events relate to authorized useof the property. The ignore and stop alerting control 760 receives userinput to indicate that the user would like to ignore the abnormalactivity alert and also that the user would like to stop receivingalerts related to abnormal activity.

FIG. 8 illustrates an example process 800 for determining an abnormalityscore and using the abnormality score in deciding whether to take actionin response to potentially abnormal activity at a monitored property.The process 800 may be used in taking action related to the monitoringsystem based on the detected patterns of recurring events referencedabove with respect to reference numeral 340.

The system 200 assigns scores to rules related to detected patterns(810). For instance, the system 200 determines an abnormality score toassign to each rule based on how abnormal it is for the one or moreevents that trigger the rule to occur. The system 200 may determine theabnormality score based on the confidence in the pattern that led to therule being suggested or automatically set. The system 200 stores theassigned scores in association with the rules.

FIG. 9 illustrates an example data record 900 that stores rules andabnormality scores for each of the rules. The data record 900 includes afirst column 910 for a rule used in assessing whether sensor activity isabnormal and a second column 920 for an abnormality score associatedwith the rule stored in the column 910. As shown, a first rule 930indicates that the system 200 considers activity on Saturday between 7AM and 1 PM to be abnormal. The first rule 930 has an abnormality scoreof 0.1, which indicates that the rule has a relatively low contributionto detection of abnormal activity. The abnormality score for the firstrule 930 may be set based on the first detected pattern 430 describedabove with respect to FIG. 4. The abnormality scores may be normalizedto values between −1.0 to 1.0.

A second rule 935 indicates that the system 200 considers activity onSunday between 8 AM and 12 PM to be abnormal. The second rule 935 has anabnormality score of 0.2, which indicates that the rule has a relativelylow contribution to detection of abnormal activity. The abnormalityscore for the second rule 935 may be set based on the sixth detectedpattern 480 described above with respect to FIG. 4.

A third rule 940 indicates that the system 200 considers activity onMonday to Thursday between 9 AM and 5 PM to be abnormal. The third rule940 has an abnormality score of 0.4, which indicates that the rule has arelatively medium contribution to detection of abnormal activity.

A fourth rule 945 indicates that the system 200 considers a windowopening event that is not preceded by an interior motion sensor event tobe abnormal. The fourth rule 945 has an abnormality score of 1.0, whichindicates that the rule has a relatively high contribution to detectionof abnormal activity. The abnormality score for the fourth rule 945 maybe set based on the fourth detected pattern 460 described above withrespect to FIG. 4.

A fifth rule 950 indicates that the system 200 considers a door openingevent followed by interior motion detection between 11 PM to 6 AM to beabnormal. The fifth rule 950 has an abnormality score of 0.8, whichindicates that the rule has a relatively high contribution to detectionof abnormal activity.

A sixth rule 955 indicates that the system 200 considers a user'slocation being away from home as contributing to activity at the homebeing considered as abnormal. The sixth rule 955 has an abnormalityscore of 0.2, which indicates that the rule has a relatively lowcontribution to detection of abnormal activity.

A seventh rule 960 indicates that the system 200 considers a user'slocation being at home as contributing against activity at the homebeing considered as abnormal. The seventh rule 960 has an abnormalityscore of −0.6, which indicates that the rule has a relatively mediumcontribution to detection of activity as being normal.

An eighth rule 965 indicates that the system 200 considers a user'srecent trend of ignoring abnormal activity alerts as contributingagainst activity at the home being considered as abnormal. The eighthrule 965 has an abnormality score of −0.2, which indicates that the rulehas a relatively low contribution to detection of activity as beingnormal.

Referring again to FIG. 8, the system 200 compares detected events tothe rules related to detected patterns (820). For instance, the system200 detects sensor events captured by sensors located at the property ofthe user and compares the sensor events to the rules. The system 200also may detect user location events and compare the user locationevents to the rules. The system 200 further may detect user input events(e.g., decisions to ignore abnormal activity) and compare the user inputevents to the rules.

Based on the comparison, the system 200 identifies one or more eventsthat meet one or more of the rules (830) and accesses scores associatedwith the one or more rules (840). For example, the system 200 determineswhether the sensor events, the user location events, and the user inputevents match any of the rules related to detected patterns (e.g., therule stored in the data record 900). In this example, for each matchingrule, the system 200 accesses the abnormality score assigned to therule.

The system 200 combines the accessed scores to determine an abnormalityscore for the detected events (850). For instance, the system 200 maysum all of the accessed scores to determine a total abnormality score.Other techniques for combining the accessed scores using weights orother mathematical or statistical processed may be used.

The system 200 compares the abnormality score to a threshold (860) and,based on the comparison, the system 200 determines whether theabnormality score meets the threshold (870). For instance, the system200 accesses the threshold and compares the abnormality score to theaccessed threshold to determine whether the abnormality score is lessthan, equal to, or greater than the threshold. The system 200 maydetermine that the threshold is met using any of the determinationsdepending on the implementation, such as determining that the thresholdis met based on the abnormality score being greater than the thresholdor determining that the threshold is met based on the abnormality scorebeing greater than or equal to the threshold.

Based on a determination that the abnormality score meets the threshold,the system 200 takes action for abnormal activity (880). For example,the system 200 sends an alert to the user to indicate detection ofabnormal activity that meets the threshold. In this example, the system200 may send an alert having content similar to that included in theinterface 700 described above with respect to FIG. 7.

Based on a determination that the abnormality score does not meet thethreshold, the system 200 continues monitoring detected events andupdates the abnormality score based on newly detected events and timingof newly detected events (890). For example, the system 200 continues todetermine whether newly detected events meet any of the rules, accessesscores for any rules that match the newly detected events, and updatesthe abnormality score based on the accessed scores for the newlydetected events. In this example, the system 200 may add the accessedscores for the newly detected events to the abnormality score anddetermine whether the new abnormality score reaches the threshold ornot.

In addition, the system 200 may consider the timing of the newlydetected events in updating the abnormality score. For instance,slightly abnormal events that are detected far apart in terms of timingare unlikely to signal abnormal activity. Accordingly, the system 200may periodically decrement the abnormality score a certain amount (e.g.,decrement the abnormality score by 0.2 every hour). In this regard, thedecrementing of the abnormality score reduces the chance of abnormalactivity being detected based on slightly abnormal events that arespaced far apart in terms of time.

In some implementations, the system 200 may compute a new abnormalityscore each time a new rule is violated. In these implementations, thesystem 200 may compute the new abnormality score based on an abnormalitymeasure for the new rule violation in addition to abnormality measuresfor any rules that were violated within a threshold period of time(e.g., two hours) of the new rule violation. In this regard, the system200 only considers events that have occurred relatively closely in timein determining whether the events suggest abnormal activity.

FIG. 10 illustrates an example process 1000 for updating how detectedpatterns are used in performing monitoring system actions based on userinput. The system 200 receives user input related to use of patterns inperforming monitoring system actions (1010). For example, the system 200may receive input indicating the user's general preference for alertingrelative to how the system 200 has been alerting the user to abnormalactivity. In this example, the system 200 may receive input indicatingthat the user would like to be alerted more frequently or inputindicating the user would like to be alerted less frequently.

In some implementations, the system 200 may receive input related tospecific rules or patterns being used by the system 200. In theseimplementations, the system may receive input to confirm, delete, ormodify specific rules or patterns that are used by the system 200.

Based on the user input, the system 200 updates settings related tousing patterns to perform monitoring system actions (1020). For example,when the user input indicates the user's general preference for alertingrelative to how the system 200 has been alerting the user to abnormalactivity, the system 200 updates general settings that apply to alldetected patterns and all rules set based on detected patterns. In thisexample, the system 200 may modify an abnormality threshold used indetecting abnormal activity based on input indicating that the userwould like to be alerted more or less frequently. The system 200 alsomay uniformly modify the abnormality measures or scores assigned to allof the individual rules or detected patterns based on input indicatingthat the user would like to be alerted more or less frequently. Thesystem 200 further may uniformly modify the confidence level needed todetect a pattern based on input indicating that the user would like tobe alerted more or less frequently.

In implementations in which the user input relates to specific rules orpatterns being used by the system 200, the system 200 updates settingsfor the specific rules or patterns. For instance, in accordance with theuser input, the system 200 may modify abnormality measures or scoresassigned to the specific rules or patterns and may modify the specificrules or patterns by adding, removing, and/or changing criteria formeeting the specific rules or patterns and/or changing actions takenwhen the specific rules or patterns have been met.

The system 200 uses patterns to perform monitoring system actions basedon the updated settings (1030). For instance, the system 200 may use theupdated setting in any of the techniques described throughout thisdisclosure for taking action related to the monitoring system based onthe detected patterns of recurring events.

FIG. 11 illustrates an example interface 1100 that enables a user toadjust settings related to using patterns to perform monitoring systemactions. The interface 1100 may be part of a message (e.g., electronicmail message) sent to a device of a user of a monitoring system or maybe displayed when the user of the monitoring system accesses a web pageassociated with the monitoring system. The system 200 may cause displayof the interface 1100 when new patterns of recurring events have beendetected and new rules automatically set. The system 200 may causedisplay of the interface 1100 as part of receiving user input related touse of patterns in performing monitoring system actions described abovewith respect to reference numeral 1010.

The interface 1100 includes a just right control 1110, an alert me morecontrol 1120, an alert me less control 1130, and a stop alerting control1140. The controls 1110-1140 enable a user to provide input indicatingthe user's general preference for alerting. The just right control 1110receives input to indicate that the user is satisfied with the alertingthat has been provided and would like the alerting to continue in thesame manner. In response to receiving user input selecting the justright control 1110, the system 200 maintains settings related to usingpatterns to perform monitoring system actions without changes.

The alert me more control 1120 receives input to indicate that the userwould like to be alerted more to detections of potentially abnormalactivity. In response to receiving user input selecting the alert memore control 1120, the system 200 adjusts settings related to usingpatterns to perform monitoring system actions in a manner that wouldgenerate more alerts based on potentially abnormal activity. Forinstance, the system 200 may lower an abnormality score threshold usedin determining whether to send an alert for abnormal activity. Bylowering the threshold, the system 200 sends alerts based on a lowerlevel of abnormal activity, thereby resulting in more alerts. Inaddition, the system 200 may lower a confidence level needed to detect apattern of activity. By lowering the confidence level needed to detect apattern of activity, the system 200 may detect patterns more quicklywith less confidence and, therefore, result in alerts for more potentialpatterns of activity.

The alert me less control 1130 receives input to indicate that the userwould like to be alerted less to detections of potentially abnormalactivity. In response to receiving user input selecting the alert meless control 1130, the system 200 adjusts settings related to usingpatterns to perform monitoring system actions in a manner that wouldgenerate fewer alerts based on potentially abnormal activity. Forinstance, the system 200 may increase an abnormality score thresholdused in determining whether to send an alert for abnormal activity. Byincreasing the threshold, the system 200 sends alerts based on a higherlevel of abnormal activity, thereby resulting in fewer alerts. Inaddition, the system 200 may raise a confidence level needed to detect apattern of activity. By raising the confidence level needed to detect apattern of activity, the system 200 may take longer to detect patternsand do so with higher confidence, thereby resulting in alerts for fewerpotential patterns of activity.

The stop alerting control 1140 receives input to indicate that the userdoes not wish to receive any alerts related to abnormal activitydetected using patterns of recurring events. In response to receivinguser input selecting the stop alerting control 1140, the system 200stops detecting patterns and stops providing alerts to the user based ondetected patterns.

In addition, the interface 1100 includes a list of automatically setrules 1150 and a confidence 1160 that reflects a level of confidence ofthe system 200 in automatically setting the rule. The interface 1100also includes a confirm control 1170, a remove control 1172, and amodify control 1174 for a first automatically set rule and a confirmcontrol 1180, a remove control 1182, and a modify control 1184 for asecond automatically set rule. The list 1150 and the confidence 1160 aresimilar to the list 610 and the confidence 620 described above withrespect to FIG. 6. The confirm controls 1170 and 1180, the removecontrols 1172 and 1182, and the modify controls 1182 and 1184 aresimilar to the confirm controls 630 and 640, the remove controls 632 and642, and the modify controls 634 and 644 described above with respect toFIG. 6. Inclusion of the confirm controls 1170 and 1180, the removecontrols 1172 and 1182, and the modify controls 1182 and 1184 in theinterface 1100 allow a user to provide input on specific automaticallyset rules in addition to (or instead of) input indicating the user'sgeneral preference for alerting provided through controls 1110-1140.

FIG. 12 illustrates an example process 1200 for updating rules used intaking action for abnormal events. The system 200 tracks additionalevents after storing data related to taking action based on detectedpatterns (1210). For example, after performing analysis to detectpatterns and set rules for the monitoring system, the system 200 tracksadditional events. In this example, the additional events may beadditional sensor events detected by sensors located at the monitoredproperty, additional user location events that track a location ofmobile devices of users of the monitoring system, additional user inputevents that track how the user has updated and responded to differentaction taken by the system 200 in response to detecting patterns, andany other events that are described throughout this disclosure or thatmay be helpful in detecting patterns that assist in identifying abnormalactivity. In tracking additional events, the system 200 may usetechniques similar to those described above with respect to referencenumerals 310 and 320 in FIG. 3.

The system 200 analyzes the additional events with respect to the datarelated to taking action (1220). For example, the system 200 mayperiodically analyze whether the additional events impact the patternsof recurring events previously detected by the system 200. In thisexample, the system 200 may, each month, compare additional eventsdetected over the past month with the patterns of recurring eventspreviously detected and determine whether the previously detectedpatterns still hold. The system 200 also may initiate analysis ofadditional events based on an amount of additional events trackedreaching a threshold level. In analyzing the additional events withrespect to the data related to taking action, the system 200 may usetechniques similar to those described above with respect to referencenumeral 330 in FIG. 3.

Based on the analysis, the system 200 taking action related to updatingrules used in taking action for abnormal events (1230). For instance,the system 200 may suggest updates to the rules and/or patterns used indetecting abnormal activity or may automatically make updates to therules and/or patterns used in detecting abnormal activity. In takingaction related to updating rules used in taking action for abnormalevents, the system 200 may use techniques similar to those describedabove with respect to reference numeral 340 in FIG. 3.

FIG. 13 illustrates an example interface 1300 that makes suggestions forupdating rules based on changes to detected patterns of recurringevents. The interface 1300 may be part of a message (e.g., electronicmail message) sent to a device of a user of a monitoring system or maybe displayed when the user of the monitoring system accesses a web pageassociated with the monitoring system. The system 200 may cause displayof the interface 1300 when new events are detected that impactpreviously recognized patterns of recurring events. The system 200 maycause display of the interface 1300 as part of taking action related toupdating rules used in taking action for abnormal events described abovewith respect to reference numeral 1230.

As shown, the interface 1300 includes a list of suggested rulemodifications 1310 and a confidence 1320 that reflects a level ofconfidence the system 200 has in the rule. The confidence 1320 mayassist a user in determining whether or not to adjust a rule that hasbeen set. A first suggested rule modification is to remove or suspend anotification alert that occurs when the system 200 detects activity onSunday between eight in the morning and noon. The interface 1300 showsthat the confidence level in the rule has dropped from seventy to forty,which may indicate that the pattern that initially resulted in the rulebeing suggested or automatically set has dropped from occurring seventypercent of the time to only occurring forty percent of the time based onnew events detected by the system 200 that conflict with the pattern.

The interface 1300 includes a delete control 1330 that receives input todelete the rule associated with the first suggested rule modification.The interface 1300 also includes a suspend control 1332 that receivesinput to suspend the rule associated with the first suggested rulemodification. The suspend control 1332 may cause the rule to besuspended for a predefined period of time (e.g., one month), may causethe rule to be suspended until the confidence in the rule returns to athreshold level of confidence (e.g., returns to seventy), or may promptthe user for additional input to define the period of time for which therule should be suspended. The interface 1300 further includes a modifycontrol 1334 that receives input to retain the rule associated with thefirst suggested rule modification, but in a modified format. The modifycontrol 1334 may cause display of another interface that enables a userto provide input to modify the rule associated with the first suggestedrule modification by adding, removing, and/or changing criteria formeeting the rule and/or changing actions taken when the rule has beenmet. The user also may ignore the suggestions made in the interface 1300and, thereby, confirm that the rule associated with the first suggestedrule modification should be retained in its current form. The system 200may consider decisions to delete, suspend, modify, and confirm the ruleassociated with the first suggested rule modification in futuresuggestions made to the user.

FIG. 14 illustrates an example interface 1400 that alerts a user toadjustments automatically made to rules set for a monitoring systembased on changes to detected patterns of recurring events. The system200 may automatically make the rule adjustments without humanintervention or any user input. The interface 1400 may be part of amessage (e.g., electronic mail message) sent to a device of a user of amonitoring system or may be displayed when the user of the monitoringsystem accesses a web page associated with the monitoring system. Thesystem 200 may cause display of the interface 1400 when new events aredetected that impact previously recognized patterns of recurring eventsand cause automatic adjustments to rules. The system 200 may causedisplay of the interface 1400 as part of taking action related toupdating rules used in taking action for abnormal events described abovewith respect to reference numeral 1230.

As shown, the interface 1400 includes a list of automatic adjustments1410 and a confidence 1420 that reflects a level of confidence of thesystem 200 has in the rule. The confidence 1420 may assist a user indetermining whether or not to confirm or decline an automaticadjustment. A first rule considered activity on Saturday between 7 AMand 1 PM to be abnormal. The system 200 has automatically deleted thefirst rule by deleting an abnormality score assigned to the first rule.The system 200 automatically deleted the first rule because theconfidence level in the rule has dropped from sixty to forty, which mayindicate that the pattern that initially resulted in the rule beingsuggested or automatically set has dropped from occurring sixty percentof the time to only occurring forty percent of the time based on newevents detected by the system 200 that conflict with the pattern.

The interface 1400 includes a confirm control 1430 that receives inputto confirm that the first rule should be deleted. The interface 1400also includes a decline control 1432 that receives input to decline theautomatic adjustment and maintain the first rule. The interface 1400further includes a modify control 1434 that receives input to confirmthat the first rule should be adjusted, but in a different way. Themodify control 1434 may cause display of another interface that enablesa user to provide input to modify the first rule by adding, removing,and/or changing criteria for meeting the rule and/or changing actionstaken when the rule has been met. The system 200 may consider decisionsto confirm, decline, and modify the adjustment to the first rule infuture automatic adjustment of rules for the monitoring system of theuser.

A second rule considered detection of a window opening event that is notpreceded by an interior motion sensor event to be highly abnormal. Thesecond rule was assigned an abnormality score of 1.0 to reflect the highdegree of abnormality associated with the second rule. The system 200has automatically reduced the abnormality score assigned to the secondrule from 1.0 to 0.8. The system 200 automatically reduced theabnormality score for the second rule because the confidence level inthe rule has dropped from one hundred to ninety-five, which may indicatethat the pattern that initially resulted in the rule being suggested orautomatically set has dropped from occurring one hundred percent of thetime to only occurring ninety-five percent of the time based on newevents detected by the system 200 that conflict with the pattern.

The interface 1400 includes a confirm control 1440 that receives inputto confirm that the abnormality score for the second rule should bereduced. The interface 1400 also includes a decline control 1442 thatreceives input to decline the automatic adjustment and maintain theabnormality score for the second rule. The interface 1400 furtherincludes a modify control 1444 that receives input to confirm that theabnormality score for the second rule should be adjusted, but in adifferent way. The modify control 1444 may cause display of anotherinterface that enables a user to provide input to modify the second ruleby adding, removing, and/or changing criteria for meeting the ruleand/or changing actions taken when the rule has been met. The system 200may consider decisions to confirm, decline, and modify the adjustment tothe second rule in future automatic adjustment of rules for themonitoring system of the user.

The described systems, methods, and techniques may be implemented indigital electronic circuitry, computer hardware, firmware, software, orin combinations of these elements. Apparatus implementing thesetechniques may include appropriate input and output devices, a computerprocessor, and a computer program product tangibly embodied in amachine-readable storage device for execution by a programmableprocessor. A process implementing these techniques may be performed by aprogrammable processor executing a program of instructions to performdesired functions by operating on input data and generating appropriateoutput. The techniques may be implemented in one or more computerprograms that are executable on a programmable system including at leastone programmable processor coupled to receive data and instructionsfrom, and to transmit data and instructions to, a data storage system,at least one input device, and at least one output device. Each computerprogram may be implemented in a high-level procedural or object-orientedprogramming language, or in assembly or machine language if desired; andin any case, the language may be a compiled or interpreted language.Suitable processors include, by way of example, both general and specialpurpose microprocessors. Generally, a processor will receiveinstructions and data from a read-only memory and/or a random accessmemory. Storage devices suitable for tangibly embodying computer programinstructions and data include all forms of non-volatile memory,including by way of example semiconductor memory devices, such asErasable Programmable Read-Only Memory (EPROM), Electrically ErasableProgrammable Read-Only Memory (EEPROM), and flash memory devices;magnetic disks such as internal hard disks and removable disks;magneto-optical disks; and Compact Disc Read-Only Memory (CD-ROM). Anyof the foregoing may be supplemented by, or incorporated in,specially-designed ASICs (application-specific integrated circuits).

It will be understood that various modifications may be made. Forexample, other useful implementations could be achieved if steps of thedisclosed techniques were performed in a different order and/or ifcomponents in the disclosed systems were combined in a different mannerand/or replaced or supplemented by other components. Accordingly, otherimplementations are within the scope of the disclosure.

What is claimed is:
 1. An electronic system comprising: at least oneprocessor; and at least one non-transitory computer-readable storagemedium coupled to the at least one processor having stored thereoninstructions which, when executed by the at least one processor, causesthe at least one processor to perform operations comprising: collectingdata sensed by a monitoring system that monitors a property of a user;aggregating the collected data over a period of a time; detecting,within the aggregated data, patterns of recurring events; and based ondetecting the patterns of recurring events within the aggregated data,taking action related to the monitoring system based on the detectedpatterns of recurring events within the aggregated data, wherein takingaction related to the monitoring system based on the detected patternsof recurring events within the aggregated data comprises: determining tosuggest a rule for the monitoring system based on the detected patternsof recurring events within the aggregated data; sending, to the user ofthe monitoring system, a suggestion of the rule for the monitoringsystem, the suggestion including an interface that includes adescription of the rule being suggested and interface controls thatenable the user of the monitoring system to set the rule for themonitoring system, decline the rule for the monitoring system, or set amodified version of the rule for the monitoring system; receiving userinput provided through at least one of the interface controls includedin the interface that indicates how the user of the monitoring systemwould like to handle the rule being suggested; and handling the rule forthe monitoring system based on the received user input that indicateshow the user of the monitoring system would like to handle the rulebeing suggested.
 2. The electronic system of claim 1, wherein detecting,within the aggregated data, patterns of recurring events comprises:detecting, within the aggregated data, a series of events that have beenrepeated multiple times; determining a confidence score associated withthe series of events that reflects whether repetition of the series ofevents is a recurring pattern; comparing the determined confidence scoreto a threshold; based on the comparison, determining that the determinedconfidence score meets the threshold; and detecting the series of eventsas a pattern of recurring events based on the determination that thedetermined confidence score meets the threshold.
 3. The electronicsystem of claim 1: wherein determining to suggest the rule for themonitoring system based on the detected patterns of recurring eventswithin the aggregated data comprises determining to suggest anotification alert that notifies the user in response to data sensed bythe monitoring system indicating activity that is inconsistent with thedetected patterns of recurring events within the aggregated data; andwherein sending, to the user of the monitoring system, the suggestion ofthe rule for the monitoring system comprises sending, to the user of themonitoring system, a suggestion of the notification alert that notifiesthe user in response to data sensed by the monitoring system indicatingactivity that is inconsistent with the detected patterns of recurringevents within the aggregated data.
 4. The electronic system of claim 1,wherein the operations further comprise: receiving user input related touse of patterns of recurring events in performing actions related to themonitoring system; based on the user input, updating settings thatcontrol use of patterns of recurring events in performing actionsrelated to the monitoring system; and using patterns of recurring eventsto perform actions related to the monitoring system based on the updatedsettings.
 5. The electronic system of claim 1, wherein the operationsfurther comprise: tracking additional events after storing data relatedto taking action based on the detected patterns of recurring events;analyzing the additional events with respect to the data related totaking action based on the detected patterns of recurring events; andbased on the analysis, taking action related to updating rules used intaking action for abnormal events.
 6. The electronic system of claim 1:wherein collecting data sensed by the monitoring system that monitorsthe property of the user comprises collecting historical sensor datacaptured by sensors of the monitoring system that are fixed at theproperty and that sense events at the property, collecting location datafor the user that reflects a location of the user relative to events atthe property sensed by the monitoring system, and collecting historicalresponses by the user to alerts provided automatically based on thedetected patterns of recurring events within the aggregated data;wherein aggregating the collected data over a period of a time comprisesaggregating, over a period of time, the collected historical sensordata, the collected location data, and the collected historicalresponses; wherein detecting, within the aggregated data, patterns ofrecurring events comprises detecting patterns of recurring events withinthe collected historical sensor data, the collected location data, andthe collected historical responses; and wherein taking action related tothe monitoring system based on the detected patterns of recurring eventswithin the aggregated data comprises taking action related to themonitoring system based on a current status of the monitoring system, auser-specified level of sensitivity for each sensor and a measure of howmuch false alarms bother them, and the detected patterns of recurringevents within the collected historical sensor data, the collectedlocation data, and the collected historical responses.
 7. The electronicsystem of claim 1: wherein detecting, within the aggregated data,patterns of recurring events comprises detecting timing patterns ofrecurring events within the aggregated data and detecting order patternsrelated to an order in which recurring events occur; and wherein takingaction related to the monitoring system based on the detected patternsof recurring events within the aggregated data comprises taking actionrelated to the monitoring system based on the detected timing patternsof recurring events within the aggregated data and the detected orderpatterns related to the order in which recurring events occur.
 8. Theelectronic system of claim 1, wherein sending, to the user of themonitoring system, the suggestion of the rule for the monitoring systemcomprises: determining a confidence score for the rule being suggested;and including the determined confidence score for the rule beingsuggested in the interface with the description of the rule beingsuggested and the interface controls that enable the user of themonitoring system to set the rule for the monitoring system, decline therule for the monitoring system, or set a modified version of the rulefor the monitoring system.
 9. The electronic system of claim 1, whereinsending, to the user of the monitoring system, the suggestion of therule for the monitoring system comprises: determining a number of alertsthat the rule being suggested is expected to generate over a period oftime; and including the determined number of alerts that the rule beingsuggested is expected to generate over the period of time in theinterface with the description of the rule being suggested and theinterface controls that enable the user of the monitoring system to setthe rule for the monitoring system, decline the rule for the monitoringsystem, or set a modified version of the rule for the monitoring system.10. An electronic system comprising: at least one processor; and atleast one non-transitory computer-readable storage medium coupled to theat least one processor having stored thereon instructions which, whenexecuted by the at least one processor, causes the at least oneprocessor to perform operations comprising: collecting data sensed by amonitoring system that monitors a property of a user; aggregating thecollected data over a period of a time; detecting, within the aggregateddata, patterns of recurring events; based on detecting the patterns ofrecurring events within the aggregated data, taking action related tothe monitoring system; receiving user input related to use of patternsof recurring events in performing actions related to the monitoringsystem; based on the user input, updating settings that control use ofpatterns of recurring events in performing actions related to themonitoring system; and using patterns of recurring events to performactions related to the monitoring system based on the updated settings,wherein receiving user input related to use of patterns of recurringevents in performing actions related to the monitoring system comprisesreceiving user input indicating that the user would like to be alertedmore based on patterns of recurring events; wherein updating settingsthat control use of patterns of recurring events in performing actionsrelated to the monitoring system comprises updating settings to decreasea level of confidence of detected activity being abnormal activityneeded to alert the user of abnormal activity; and where using patternsof recurring events to perform actions related to the monitoring systembased on the updated settings comprises using patterns of recurringevents to perform actions in accordance with the decreased level ofconfidence.
 11. An electronic system comprising: at least one processor;and at least one non-transitory computer-readable storage medium coupledto the at least one processor having stored thereon instructions which,when executed by the at least one processor, causes the at least oneprocessor to perform operations comprising: collecting data sensed by amonitoring system that monitors a property of a user; aggregating thecollected data over a period of a time; detecting, within the aggregateddata, patterns of recurring events; based on detecting the patterns ofrecurring events within the aggregated data, taking action related tothe monitoring system; receiving user input related to use of patternsof recurring events in performing actions related to the monitoringsystem; based on the user input, updating settings that control use ofpatterns of recurring events in performing actions related to themonitoring system; and using patterns of recurring events to performactions related to the monitoring system based on the updated settings,wherein receiving user input related to use of patterns of recurringevents in performing actions related to the monitoring system comprisesreceiving user input indicating that the user would like to be alertedless based on patterns of recurring events; wherein updating settingsthat control use of patterns of recurring events in performing actionsrelated to the monitoring system comprises updating settings to increasea level of confidence of detected activity being abnormal activityneeded to alert the user of abnormal activity; and where using patternsof recurring events to perform actions related to the monitoring systembased on the updated settings comprises using patterns of recurringevents to perform actions in accordance with the increased level ofconfidence.
 12. The electronic system of claim 11, wherein taking actionrelated to the monitoring system based on the detected patterns ofrecurring events within the aggregated data comprises automatically,without action by the user, setting a rule for the monitoring systembased on the detected patterns of recurring events within the aggregateddata.
 13. The electronic system of claim 12, wherein automatically,without action by the user, setting the rule for the monitoring systembased on the detected patterns of recurring events within the aggregateddata comprises automatically, without action by the user, setting anotification alert that notifies the user in response to data sensed bythe monitoring system indicating activity that is inconsistent with thedetected patterns of recurring events within the aggregated data. 14.The electronic system of claim 12, wherein automatically, without actionby the user, setting the rule for the monitoring system based on thedetected patterns of recurring events within the aggregated datacomprises automatically, without action by the user, extending a dialerdelay for an alarm condition detected by the monitoring system based onactivity that is consistent with the detected patterns of recurringevents within the aggregated data, but that occurs at a time when themonitoring system is armed, the dialer delay being a time period duringwhich the user is able to deactivate the alarm condition prior to themonitoring system notifying a central monitoring station about the alarmcondition.
 15. The electronic system of claim 11, wherein taking actionrelated to the monitoring system based on the detected patterns ofrecurring events within the aggregated data comprises sending, to theuser and at a time when the monitoring system is in an unarmed state, anotification alert that notifies the user that data sensed by themonitoring system indicates activity that is inconsistent with thedetected patterns of recurring events within the aggregated data. 16.The electronic system of claim 11, wherein taking action related to themonitoring system based on the detected patterns of recurring eventswithin the aggregated data comprises sending, to a central monitoringstation and at a time when the monitoring system is in an unarmed state,an alarm notification that notifies the central monitoring station of apotential alarm condition based on data sensed by the monitoring systemindicating activity that is inconsistent with the detected patterns ofrecurring events within the aggregated data, the central monitoringstation being authorized to dispatch emergency services based on alarmconditions detected by the monitoring system.
 17. The electronic systemof claim 11, wherein taking action related to the monitoring systembased on the detected patterns of recurring events within the aggregateddata comprises: identifying a series of events detected by themonitoring system; determining abnormality measures based on thedetected patterns of recurring events within the aggregated data, thedetermined abnormality measures including an abnormality measure foreach event included in the series of events; determining an abnormalityscore for the series of events based on the determined abnormalitymeasures; comparing the abnormality score to a threshold; based on thecomparison, determining that the abnormality score meets the threshold;and based on the determination that the abnormality score meets thethreshold, sending, to the user, an alert indicating that the monitoringsystem has detected abnormal activity at the property of the user. 18.The electronic system of claim 11, wherein taking action related to themonitoring system based on the detected patterns of recurring eventswithin the aggregated data comprises: assigning scores to rules relatedto the detected patterns of recurring events within the aggregated data;comparing events detected by the monitoring system to the rules relatedto the detected patterns of recurring events within the aggregated data;based on the comparison, identifying one or more events that meet atleast two of the rules; based on identifying the one or more events thatmeet the at least two rules, accessing scores associated with the atleast two rules; combining the accessed scores to determine anabnormality score for the events detected by the monitoring system;comparing the abnormality score to a threshold; based on the comparison,determining that the abnormality score meets the threshold; and based onthe determination that the abnormality score meets the threshold, takingaction for abnormal activity detected by the monitoring system.
 19. Theelectronic system of claim 11, wherein taking action related to themonitoring system based on the detected patterns of recurring eventswithin the aggregated data comprises: assigning scores to rules relatedto the detected patterns of recurring events within the aggregated data;comparing events detected by the monitoring system to the rules relatedto the detected patterns of recurring events within the aggregated data;based on the comparison, identifying one or more events that meet atleast two of the rules; based on identifying the one or more events thatmeet the at least two rules, accessing scores associated with the atleast two rules; combining the accessed scores to determine anabnormality score for the events detected by the monitoring system;comparing the abnormality score to a threshold; based on the comparison,determining that the abnormality score does not meet the threshold; andbased on the determination that the abnormality score does not meet thethreshold, continuing to monitor events detected by the monitoringsystem and updating the abnormality score based on events newly detectedby the monitoring system and timing of the events newly detected by themonitoring system.
 20. The electronic system of claim 11, whereinreceiving user input indicating that the user would like to be alertedless based on patterns of recurring events comprises: presenting aninterface that requests feedback on how the monitoring system hasperformed in taking action based on patterns of recurring events andthat includes interface controls that enable a user to indicate that theuser would like the monitoring system to continue taking action as ithas been, that the user would like to be alerted less by the monitoringsystem, that the user would like to be alerted more by the monitoringsystem, or that the user would like the monitoring system to stop takingaction; and receiving, through the presented interface, user inputprovided using at least one of the interface controls that indicatesthat the user would like to be alerted less by the monitoring system.21. The electronic system of claim 11, wherein detecting, within theaggregated data, patterns of recurring events comprises: detecting,within the aggregated data, a series of events that have been repeatedmultiple times; determining a confidence score associated with theseries of events that reflects whether repetition of the series ofevents is a recurring pattern; comparing the determined confidence scoreto a threshold; based on the comparison, determining that the determinedconfidence score meets the threshold; and detecting the series of eventsas a pattern of recurring events based on the determination that thedetermined confidence score meets the threshold.
 22. The electronicsystem of claim 11: wherein detecting, within the aggregated data,patterns of recurring events comprises detecting timing patterns ofrecurring events within the aggregated data and detecting order patternsrelated to an order in which recurring events occur; and wherein takingaction related to the monitoring system based on the detected patternsof recurring events within the aggregated data comprises taking actionrelated to the monitoring system based on the detected timing patternsof recurring events within the aggregated data and the detected orderpatterns related to the order in which recurring events occur.